Who you are

• This position requires a balance of deep technical expertise, strong analytical thinking, and cross-functional collaboration
• 3–5+ years of professional experience developing, training, validating, and deploying deep learning-based perception models for ADAS or related computer vision applications
• In-depth understanding of training and inference pipelines, including data loading, augmentation, and loss function design
• Advanced degree (M.S. or Ph.D.) in Computer Vision, Robotics, Machine Learning, or a closely related discipline, or equivalent industry experience
• Strong proficiency in Python and a deep understanding of software design principles and development best practices
• Expertise in PyTorch (preferred) or TensorFlow for large-scale model development and experimentation
• Practical experience with data pipelines, distributed training, and machine learning experiment management tools
• Proven ability to work effectively in a collaborative, cross-functional team environment
• Comprehensive understanding of machine learning algorithms, including classification, regression, and clustering methods
• Experience deploying and optimizing models for embedded or automotive SoCs (e.g., NVIDIA Drive, TI TDA4, Qualcomm Snapdragon)
• Proficiency in model optimization techniques such as quantization, pruning, and knowledge distillation
• Doctorate (Ph.D.) in Computer Science, Artificial Intelligence, or related field is a plus
• Strong programming experience in Python and/or C++ within Linux development environments
• Familiarity with automotive perception workflows, datasets, and evaluation frameworks (e.g., KITTI, Waymo, Euro NCAP)

What the job involves

• We are seeking a highly skilled Senior Deep Learning Engineer to drive the development and deployment of advanced perception models for Advanced Driver Assistance Systems (ADAS)
• The successful candidate will play a key role in designing cutting-edge neural network architectures, optimizing model performance, and ensuring reliable deployment on embedded platforms